Errors and Warnings
What are Errors and Warnings
Errors and warnings are ways of notifying users that they system is observing something it believes is incorrect. Errors are meant to identify more serious issues that could break models or cause significant inaccuracies. Warnings are meant to alert the user that something is not being used as intended and to move forward with discretion.
The why and the how
When compiling code in computer languages, they usually alert the software engineer to errors and warnings it observes. Our system will behave in the same way. When models are built or tables are created they should be connected to errors and warnings so teams utilizing them can be notified if something is wrong. These systems can, and should be updated each time a new issue is observed.
Clearly notify the user
The two best places to notify a user that an error or warning has occurred are in the cell itself and in a notification box with the sum of observed warnings and errors. This creates a clear visualization that something should be reviewed for accuracy. This is similar to how misspelled words have a red line under them in most writing software. By also having a sum total of all warnings and errors, a user can clearly see whether they have fixed all of them or that they may have missed some.
Explain each error and warning
Always explain what different errors mean and, if possible, suggest how to fix them.
By creating a clear indication of not only what each error means but also including its location and possible suggestions on how to solve it you give team members more ability to solve their problems without them needing to go to annalists or engineers. These explanations should continuously be updated to best support the operators of the models.
Related Information
Pre-test modeling
The examples used in this article relate to our pre-test model article on better understanding the potential difficulties and impacts a test may have.